A tree metric using structure and length to capture distinct phylogenetic signals

TL;DR

This paper introduces a new tree metric that combines structure and length to effectively compare phylogenetic trees, aiding in visualization, analysis, and selection of well-supported evolutionary hypotheses.

Contribution

A novel metric for rooted, labeled trees that captures both structure and branch length, enabling robust comparison and visualization of phylogenetic trees from diverse data sources.

Findings

Enables clear visualization of tree space.

Detects distinct topology clusters in posterior distributions.

Assists in selecting well-supported phylogenetic trees.

Abstract

Phylogenetic trees are a central tool in understanding evolution. They are typically inferred from sequence data, and capture evolutionary relationships through time. It is essential to be able to compare trees from different data sources (e.g. several genes from the same organisms) and different inference methods. We propose a new metric for robust, quantitative comparison of rooted, labeled trees. It enables clear visualizations of tree space, gives meaningful comparisons between trees, and can detect distinct islands of tree topologies in posterior distributions of trees. This makes it possible to select well-supported summary trees. We demonstrate our approach on Dengue fever phylogenies.